Dialect speech recognition for businesses
Standard speech-to-text from the big providers struggles with Niederbairisch, Oberpfälzisch, Fränkisch, Schwäbisch and Austrian German. We run a custom German ASR fine-tuning pipeline on our own dialect model instead — built for speech to text on regional accents, not against them.
The model is fine-tuned on more than 2,000 reviewed recordings collected across Bavaria via our Dialektsammler app, and can be deployed as a custom German speech recognition API — in the cloud, in the EU, or on-premise.
Use cases
Where dialect speech recognition earns its keep.
Call centers & customer hotlines
Understand callers who speak in dialect instead of routing them to a human every time standard speech-to-text fails.
Trades offices & field service
Turn voice notes about quotes and measurements (Aufmaß), dictated on-site or in the van, straight into structured text.
Records & documentation
Care homes, practices and public administration staff dictate notes and records in their own dialect instead of typing them up.
Machine & plant operation
Operate machines and equipment by voice on the shop floor, where dialect and background noise both work against standard ASR.
How we integrate it
Ways to plug the model into what you already use.
- • An API into your existing tools, for dialect speech recognition wherever your workflow already lives.
- • Batch transcription for recorded audio, and live or streaming recognition where it's technically feasible.
- • WhatsApp voice messages transcribed via our Spables integration.
- • EU hosting, and no training on your data without a separate agreement.
Recognition produces text; your workflow may also need customer matching, structured fields or a handover to an existing system. Our data platforms and pipelines cover that next step. We scope recognition, integration and ongoing operation separately, using the engagement models on our pricing page.
Why a custom model
Off-the-shelf speech-to-text is trained overwhelmingly on Hochdeutsch, so it degrades fast on regional accents. Our approach is Whisper fine-tuning on dialect recordings, served with CTranslate2 for efficient CPU and GPU inference, backed by continuous data collection through Dialektsammler. You can try the current model yourself on dia.coflnet.com — our public demo and community/contributor site where people submit dialect recordings, not a customer-facing product page.
For a useful evaluation, bring recordings that reflect your actual speakers, background noise and specialist vocabulary, together with the expected text. We can then assess recognition errors and the correction effort that remains before choosing an integration approach.
Related reading
- From WhatsApp voice notes to structured data: how small trades businesses stop retyping →
Orders, measurements and questions arrive as WhatsApp voice notes. How Spables turns them into text and tables automatically, encrypted and searchable.
- How much does custom software cost? Cost drivers, hourly rates and a requirements checklist for SMEs →
How much does custom software cost? The real cost drivers, 2026 hourly rates, fixed price vs. time & material, and a requirements checklist.
- Dialect-aware German speech recognition: why standard ASR struggles with Bavarian, and how we fine-tuned our own model →
Standard STT from Google and OpenAI struggles with Bavarian dialects. How we fine-tuned Whisper on dialect data and deployed it for enterprise use.
One-hour consultation for €150
60 minutes with one of our managing directors about your project. Within two working days you receive a written summary with a recommended approach and a rough cost and time range.
€150+ VAT
For businesses and founders.
- Request a slot
- Short written confirmation by email
- Invoice after the call
Frequently asked questions
Which dialects are supported?
The current focus is Bavarian dialects — Lower Bavarian, Upper Palatinate and neighbouring varieties — because that is where most of our reviewed recordings come from. Franconian, Swabian, Austrian German and other regions can be added with additional voice samples; the data set keeps growing through the Dialektsammler app.
How accurate is it?
Accuracy depends on the dialect and how much recorded material exists for it. Rather than quoting one number for every case, we test the model against your own recordings before you commit, so you see real performance on your use case.
Can it run in Germany / on-prem?
Yes. We offer EU hosting and on-premise deployment where that's a requirement, alongside cloud options.
What does integration cost?
That depends on scope — batch transcription, a live streaming API, or a deeper integration with your existing tools all cost differently. Book the consultation and we'll scope it with you. Book the consultation →